By definition, CBBE is the differential effect that brand knowledge has on consumer response to the marketing (specifically, the promotion) of that brand. The figure illustrates this differential effect.

Let’s say your competitor is Brand A and you are Brand B. Then, let’s say that you have very closely competing products, in terms of key functions and features that are important to customers.

Finally, let’s say you both spend approximately the same amount on promotion for your respective products, to educate and motivate customers to buy them.

All things being equal, the larger result of purchases of your product (Brand B) versus your competitor’s (Brand A) – as represented by the dollar signs “$$$” – is the measure of CBBE.

In short, you could say that your brand equity is the aggregate of that differential effect, on an annualized basis.

Or, in other words:

IF you run four major campaigns during the year,

AND sell an average of $250,000 more than your competitor each campaign,

AND spend roughly the same amount on promotion as they do,

AND use approximately the same techniques (i.e., couponing, PR, etc.),

THEN your CBBE is $1M or more, per year.

That’s one way that branding delivers value to your business.

Here’s another…

Brand value is a significant contributor to the intangible assets, specifically, what is known as goodwill, of a company.

When you look at a balance sheet, the major components include Assets, Liabilities, and what people refer to as Owner’s Equity. Assets include tangible assets (like cash, bonds, etc.) and intangible assets. Goodwill is a key intangible asset.

In accounting terms, when a company is acquired, goodwill amounts to the excess of the “purchase consideration” (the money paid to purchase the asset or business) over the total value of the assets and liabilities. It is classified as an intangible asset on the balance sheet, since it can neither be seen nor touched.

Over the past several decades, intangible assets generally – and goodwill, specifically! – have represented an increasing percentage of acquisition costs…largely, many would say, due to the growing added value that effective branding represents to a firm.

For example, new services like HYPR Brands and Narativ that provide access to large networks of brand ambassadors — who themselves are key influencers in specific categories — are becoming powerful allies to brand building.

For marketers, the key is to be committed to measuring your CBBE and be bold about arguing the business case for your brand-building programs, when it comes to budget allocation and strategic initiatives for the company.

You are the stewards for one of the most valuable assets and powerful tools that your company has in its quest to lead your market segment. Don’t forget that!

The media monetization cycle (MMC) is something that I’ve come to observe, experientially, from more than 30 years of working in information and communications technology.

In short, as the chart shows, experience has shown that new media go through three cycles of value creation: content, community, commerce.

And, while all three are essential at some level, to the medium’s success, the quest for media companies and those that build on top of the medium (like the web) is to see how quickly they can reach the commerce curve.

Knowing that all new media go through the MMC, your strategy should be to anticipate the commerce curve and build a platform for facilitating the transition from content and community as easily as possible.

For applications development and infrastructure planning, this has broad implications for everything from user ID management, to client- and server-wide applications payloads, to schema development and database distribution, and more.

Ideally, you want to build all of those things, knowing that the medium will eventually get a place where commerce is a principle driver of activity across it, if the THE principle driver.

Understanding the MMC is more important than ever, because the pace of technology adoption has become faster than ever, as reflected by the chart from Singularity.com.

If you are in a profession, like I am, where you are in the business of seeking to launch innovative new ventures that leapfrog or even transcend (a nicer way of saying “disrupt”) incumbent technologies, then the more that you build – from the very beginning – towards the inevitable maturation point of the MMC, the better positioned you will be.

Due to no particular plan, I’ve come across a number of different personal visualization tools recently.

Most of these tools are internet-related; in particular, social media related. However, some visualize data that they obtain from me directly and indirectly.

An example of a visualization where I provide the data directly is the personal survivorship assessment that is produced by the AYA mobile app. (Learn more about AYA, which my company Appconomy developed, at the producer’s website.)

In addition to the likelihood of cancer survivorship, there are many other categories one could imagine, beyond an array of just the other possible health-related visualizations. For example: continuing education, personal finance, household energy use, on and on.

Another visualization example, produced from data that I provide, is the Wordle.

The particular Wordle shown was produced by copying-and-pasting in all of the content from my two-page professional resume’. The result is a word cloud, displaying the most commonly used words larger, and the less-used words, smaller.

Wordle is cool for a couple of reasons. First, the creator is always tinkering with it, providing new kinds of layout options, font types, etc. Second, it can be applied in so many ways. A favorite of mine is to use it in a messaging audit with a team.

Step 1 of the audit is asking the team to write down and give me the messages that are most important to them. Step 2 is to ask them for the current, definitive source for their key messages, for example, their website or some other promotional tool, like their main sales brochure.

Step 3 is to copy-and-paste the content from steps 1 and 2 into two different Wordles and compare them visually. It is amazing what frequently pops out, highlighting the stark differences between desired and actual messaging. From there, work with the team begins, forming a strategy and creating a plan to achieve the desired messaging.

For the remainder of this post, I’ll stick with a few of the social media/internet-related visualizations I’ve stumbled across.

But, I’d love to hear your favorites. Especially, if you find them truly useful or just satisfying to your curiosity, without any specific actionable purpose.

The first one is from Vizify. I mention it because I’ve found it to be the most useful, because it provides a kind of visual biography.

In addition to the visualization itself, the Vizify makers provide a handy excerpt of code that you can include as a signature block graphic in your email that piques the interest of recipients.

The next one is from LinkedIn, called Inmaps. Since this one traces the connections between your various links, it takes a bit of time to process.

But once complete, it’s worth it. Not only is it an intriguing spiderweb of your connections, key implicit clusters, and their relations.

But, it is also a dense, rich, delicate arrangement of the human, professional network that you have created, in association with all of those first-connection contacts who have linked with you over the days, months, and years.

Next one is from MIT, called Immersion, based on Gmail. It’s pretty fascinating, for a couple of reasons. First, it draws connections between your various Gmail correspondence partners, which in itself is illuminating.

Second and I suspect more surprising to most, as it was for me, Immersion ranks the people with whom you collaborate the most. When I saw my rank ordered list of top collaborators, it was definitely a wake-up call.

Most noticeably, it served as a reminder of the people who have been important to me over time, even if they aren’t necessarily people with whom I’m corresponding heavily now.

Finally, I’ll highlight a tool called Personas, from the MIT Media lab. It’s about five years old and, in fact, wasn’t operating when I tried to run it recently. But, I mention it because of my admiration for the elegant output it sought to produce, given the complexity of the algorithm at its core.

To my mind, if you have ever taken a Myers-Briggs type assessment or a DISC profile, then you can think of Personas achieving a similar assessment, but based principally on the content discoverable about you on the worldwide web. Pretty neat idea.

Again, if you have a personal visualization that you’d like to share, I’d love to hear about it!

Back as the dot-com boom was getting underway, around 1998-1999, I was briefly in conversation with the Garage.com team about joining Jamin Patrick in the new Austin office.

Jamin had a distinguished career as an entrepreneur including as one of the first leaders of the Austin Technology Incubator. We’d also become friendly from living in the same neighborhood and seeing each other at our kids’ swim meets.

The process got as far as me going to Palo Alto to spend a day with the Garage team there, including Guy Kawasaki. A really great group, all around; but, I got cold feet and we went our different ways.

During the process, though, I vividly remember one of the deals that we were looking at seriously, at the time, was a dot-com play that was all about collecting lists of information and then making those lists available for sale. I can’t remember the name of the deal, but I remember that one of the principals was Jim Seymour of PC Magazine fame.

Anyhow, the deal never got off of the ground and now, looking back of course, it all seems a bit far-fetched. But, at the time, being a perpetual list collector myself, it naturally caught my fancy.

As time went on, Delicious and other list keeping and sharing websites arose. And, now, anything I don’t bookmark goes into a bit.ly link and gets tweeted out so that I more-or-less have an eternal set of lists and other unstructured data.

I was just going through some of them the other day and thought I’d share a few of my favorites.

Lastly, here’s a bonus list that is really more of a gift to the music curious: every month, Spin magazine provides from 10 to 14 songs for download, free of charge, for your iDevice. That’s a list anyone can enjoy!

Data is cool. First, its very name is both singular and plural, like sheep or fish. (And don’t get all grammatical on me, you datum-is-singular apologists.) Second, it’s so definitive – something is 57% or it isn’t. Pi is 3.14159-etc. Sure, you can argue about the data gathering, integrity, interpretation and the like. But, at least you are arguing about the objective, rather than the subjective.

But, what I really like about data is what it reveals about all things measured. It’s in that vein that I’ve been picking up a few interesting recent developments about data, measurement, and the public sector.

First, I read a really good write-up about website measurement in the Google Public sector blog. It’s a really nice case example of data analytics 101 for a website. And, just like the writer, I have had that same giddy feeling when reviewing data from a website’s traffic and other stats.

Second, there was a good write-up about the social media side of data gathering and measurement in InformationWeek. It discusses the CIA’s investment in the social media monitoring from Visible Technologies. Good stuff, but not especially unique – you can get listeners, monitoring, and semantic trending built into nGenera’s collaboration server right now.

Third, we just published our 2010 research agenda for nGenera’s Government Insight program and are excited about some of the research vectors we intend to explore. In the major topic area of “Leading in the age of unbounded data,” we expect to cover into listening, massively customized analytics, orchestrating, and methods for reaching beyond stereotypes.